topic_model.transform(docs)[0][i] is sometimes different from topic_model.transform(docs[i])[0][0]

Hello

I read https://maartengr.github.io/BERTopic/api/bertopic.html#bertopic._bertopic.BERTopic.transform and understood from the documents parameter (described as "A single document or a list of documents to predict on") that I could submit a list of documents or a single document and still receive the same result when predicting with a fitted model.

I found that this is not true. Am I overlooking something?

Below you find a minimal working example

from bertopic import BERTopic
from sklearn.datasets import fetch_20newsgroups

docs = fetch_20newsgroups(subset='all')['data'][:200]
topic_model = BERTopic().fit(docs)
topics,_=topic_model.transform(docs)

import numpy as np
topics=np.array(topics)


#calling the model with a single document several times
import tqdm

topics_single = []
for doc in tqdm.tqdm(docs):
    topic, _ = topic_model.transform([doc])
    topics_single.append(topic[0])
topics_single = np.array(topics_single)

mask_identical = topics_single == topics
percentage_equal = 100 * np.sum(mask_identical) / len(mask_identical)
print(f"{percentage_equal=}%") #returns for example about 60%, but varying


#loop till finding a different entry
for i in range(len(docs)):
    print(
        i,
        topic_model.transform(docs[i])[0][0],
        topic_model.transform([docs[i]])[0][0],
        topics[i],
        topic_model.transform(docs)[0][i],
    )
    if topic_model.transform(docs[i])[0][0] != topic_model.transform(docs)[0][i]:
        print(f"Different outcome at iteration {i}")
        break

The repeated execution with the same documents seems fine:

topics2,_=topic_model.transform(docs)
percentage_equal_executed_with_multiple_docs = 100*np.sum(np.array(topics2)==topics)/len(topics)
print(f"{percentage_equal_executed_with_multiple_docs=}%") #this gives 100%

Thank you in advance!

PS:
The python version is 3.10.12
The list of installed packages is

absl-py==1.0.0
accelerate==0.23.0
adagio==0.2.4
aiohttp==3.8.6
aiosignal==1.3.1
ansi2html==1.9.1
antlr4-python3-runtime==4.11.1
anyio==3.5.0
appdirs==1.4.4
arch==6.2.0
argon2-cffi==21.3.0
argon2-cffi-bindings==21.2.0
astor==0.8.1
asttokens==2.0.5
astunparse==1.6.3
async-timeout==4.0.3
attrs==22.1.0
audioread==3.0.1
azure-core==1.29.1
azure-cosmos==4.3.1
azure-storage-blob==12.19.0
azure-storage-file-datalake==12.14.0
backcall==0.2.0
bcrypt==3.2.0
beautifulsoup4==4.11.1
bertopic==0.16.0
black==22.6.0
bleach==4.1.0
blinker==1.4
blis==0.7.11
boto3==1.24.28
botocore==1.27.96
cachetools==5.3.2
catalogue==2.0.10
category-encoders==2.6.2
certifi==2022.12.7
cffi==1.15.1
chardet==4.0.0
charset-normalizer==2.0.4
click==8.1.7
cloudpathlib==0.16.0
cloudpickle==2.0.0
cmake==3.27.7
cmdstanpy==1.2.0
comm==0.1.2
confection==0.1.3
configparser==5.2.0
contourpy==1.0.5
cryptography==39.0.1
cycler==0.11.0
cymem==2.0.8
Cython==0.29.32
dacite==1.8.1
dash==2.14.2
dash-core-components==2.0.0
dash-html-components==2.0.0
dash-table==5.0.0
dask==2023.12.0
databricks-automl-runtime==0.2.20
databricks-cli==0.18.0
databricks-feature-engineering==0.1.2
databricks-feature-store==0.16.1
databricks-sdk==0.1.6
dataclasses-json==0.6.2
datasets==2.14.5
dbl-tempo==0.1.26
dbus-python==1.2.18
debugpy==1.6.7
decorator==5.1.1
deepspeed==0.11.1
defusedxml==0.7.1
dill==0.3.6
diskcache==5.6.3
distlib==0.3.7
distributed==2023.12.0
distro==1.7.0
distro-info==1.1+ubuntu0.1
docstring-to-markdown==0.11
dtw-python==1.3.0
einops==0.7.0
entrypoints==0.4
evaluate==0.4.1
executing==0.8.3
facets-overview==1.1.1
fastjsonschema==2.19.0
fasttext==0.9.2
filelock==3.9.0
filterpy==1.4.5
flash-attn==2.3.2
Flask==2.2.5
flatbuffers==23.5.26
fonttools==4.25.0
frozenlist==1.4.0
fs==2.4.16
fsspec==2023.6.0
fugue==0.8.7
fugue-sql-antlr==0.2.0
future==0.18.3
gast==0.4.0
gitdb==4.0.11
GitPython==3.1.27
gluonts==0.14.3
google-api-core==2.14.0
google-auth==2.21.0
google-auth-oauthlib==1.0.0
google-cloud-core==2.3.3
google-cloud-storage==2.11.0
google-crc32c==1.5.0
google-pasta==0.2.0
google-resumable-media==2.6.0
googleapis-common-protos==1.61.0
greenlet==2.0.1
grpcio==1.48.2
grpcio-status==1.48.1
gunicorn==20.1.0
gviz-api==1.10.0
h5py==3.7.0
hdbscan==0.8.33
hjson==3.1.0
hmmlearn==0.3.0
holidays==0.35
horovod==0.28.1
htmlmin==0.1.12
httplib2==0.20.2
huggingface-hub==0.16.4
idna==3.4
ImageHash==4.3.1
imbalanced-learn==0.11.0
importlib-metadata==7.0.0
importlib-resources==6.1.1
ipykernel==6.25.0
ipython==8.14.0
ipython-genutils==0.2.0
ipywidgets==7.7.2
isodate==0.6.1
itsdangerous==2.0.1
jedi==0.18.1
jeepney==0.7.1
Jinja2==3.1.2
jmespath==0.10.0
joblib==1.2.0
joblibspark==0.5.1
jsonpatch==1.33
jsonpointer==2.4
jsonschema==4.17.3
jupyter-client==7.3.4
jupyter-server==1.23.4
jupyter_core==5.2.0
jupyterlab-pygments==0.1.2
jupyterlab-widgets==1.0.0
keras==2.14.0
keras-self-attention==0.51.0
keyring==23.5.0
kiwisolver==1.4.4
kotsu==0.3.3
langchain==0.0.314
langcodes==3.3.0
langsmith==0.0.64
launchpadlib==1.10.16
lazr.restfulclient==0.14.4
lazr.uri==1.0.6
lazy_loader==0.3
libclang==15.0.6.1
librosa==0.10.1
lightgbm==4.1.0
lit==17.0.5
llvmlite==0.39.1
locket==1.0.0
lxml==4.9.1
Mako==1.2.0
Markdown==3.4.1
MarkupSafe==2.1.1
marshmallow==3.20.1
matplotlib==3.7.0
matplotlib-inline==0.1.6
mccabe==0.7.0
mistune==0.8.4
ml-dtypes==0.2.0
mlflow-skinny==2.8.0
mne==1.6.0
more-itertools==8.10.0
mpmath==1.2.1
msgpack==1.0.7
multidict==6.0.4
multimethod==1.10
multiprocess==0.70.14
murmurhash==1.0.10
mypy-extensions==0.4.3
nbclassic==0.5.2
nbclient==0.5.13
nbconvert==6.5.4
nbformat==5.7.0
nest-asyncio==1.5.6
networkx==2.8.4
ninja==1.11.1.1
nltk==3.7
nodeenv==1.8.0
notebook==6.5.2
notebook_shim==0.2.2
numba==0.56.4
numpy==1.23.5
oauthlib==3.2.0
openai==0.28.1
opt-einsum==3.3.0
packaging==22.0
pandas==1.5.3
pandocfilters==1.5.0
paramiko==2.9.2
parso==0.8.3
partd==1.4.1
pathspec==0.10.3
pathy==0.10.3
patsy==0.5.3
petastorm==0.12.1
pexpect==4.8.0
phik==0.12.3
pickleshare==0.7.5
Pillow==9.4.0
platformdirs==2.5.2
plotly==5.9.0
pluggy==1.0.0
pmdarima==2.0.3
polars==0.19.19
pooch==1.8.0
preshed==3.0.9
prompt-toolkit==3.0.36
prophet==1.1.5
protobuf==4.24.0
psutil==5.9.0
psycopg2==2.9.3
ptyprocess==0.7.0
pure-eval==0.2.2
py-cpuinfo==9.0.0
pyaml==23.9.7
pyarrow==8.0.0
pyarrow-hotfix==0.5
pyasn1==0.4.8
pyasn1-modules==0.2.8
pybind11==2.11.1
pycatch22==0.4.2
pycparser==2.21
pydantic==1.10.6
pyflakes==3.1.0
Pygments==2.11.2
PyGObject==3.42.1
PyJWT==2.3.0
pykalman-bardo==0.9.7
PyNaCl==1.5.0
pynndescent==0.5.11
pyod==1.1.2
pyodbc==4.0.32
pyparsing==3.0.9
pyright==1.1.294
pyrsistent==0.18.0
pytesseract==0.3.10
python-apt==2.4.0+ubuntu2
python-dateutil==2.8.2
python-editor==1.0.4
python-lsp-jsonrpc==1.1.1
python-lsp-server==1.8.0
pytoolconfig==1.2.5
pytz==2022.7
PyWavelets==1.4.1
PyYAML==6.0
pyzmq==23.2.0
qpd==0.4.4
regex==2022.7.9
requests==2.28.1
requests-oauthlib==1.3.1
responses==0.18.0
retrying==1.3.4
rope==1.7.0
rsa==4.9
s3transfer==0.6.2
safetensors==0.4.0
scikit-base==0.6.1
scikit-learn==1.1.1
scikit-optimize==0.9.0
scikit-posthocs==0.8.0
scipy==1.10.0
seaborn==0.12.2
seasonal==0.3.1
SecretStorage==3.3.1
Send2Trash==1.8.0
sentence-transformers==2.2.2
sentencepiece==0.1.99
shap==0.43.0
simplejson==3.17.6
six==1.16.0
skpro==2.1.1
sktime==0.24.1
slicer==0.0.7
smart-open==5.2.1
smmap==5.0.0
sniffio==1.2.0
sortedcontainers==2.4.0
soundfile==0.12.1
soupsieve==2.3.2.post1
soxr==0.3.7
spacy==3.7.1
spacy-legacy==3.0.12
spacy-loggers==1.0.5
spark-tensorflow-distributor==1.0.0
SQLAlchemy==1.4.39
sqlglot==20.2.0
sqlparse==0.4.2
srsly==2.4.8
ssh-import-id==5.11
stack-data==0.2.0
stanio==0.3.0
statsforecast==1.6.0
statsmodels==0.13.5
stumpy==1.12.0
sympy==1.11.1
tabulate==0.8.10
tangled-up-in-unicode==0.2.0
tbats==1.1.3
tblib==3.0.0
tenacity==8.1.0
tensorboard==2.14.0
tensorboard-data-server==0.7.2
tensorboard-plugin-profile==2.14.0
tensorflow==2.14.0
tensorflow-estimator==2.14.0
tensorflow-io-gcs-filesystem==0.34.0
termcolor==2.3.0
terminado==0.17.1
thinc==8.2.1
threadpoolctl==2.2.0
tiktoken==0.5.1
tinycss2==1.2.1
tokenize-rt==4.2.1
tokenizers==0.14.0
tomli==2.0.1
toolz==0.12.0
torch==2.0.1+cu118
torchvision==0.15.2+cu118
tornado==6.1
tqdm==4.64.1
traitlets==5.7.1
transformers==4.34.0
triad==0.9.3
triton==2.0.0
tsfresh==0.20.1
tslearn==0.5.3.2
typeguard==2.13.3
typer==0.9.0
typing-inspect==0.9.0
typing_extensions==4.4.0
ujson==5.4.0
umap-learn==0.5.5
unattended-upgrades==0.1
urllib3==1.26.14
virtualenv==20.16.7
visions==0.7.5
wadllib==1.3.6
wasabi==1.1.2
wcwidth==0.2.5
weasel==0.3.4
webencodings==0.5.1
websocket-client==0.58.0
Werkzeug==2.2.2
whatthepatch==1.0.2
widgetsnbextension==3.6.1
wordcloud==1.9.2
wrapt==1.14.1
xarray==2023.12.0
xgboost==1.7.6
xxhash==3.4.1
yapf==0.33.0
yarl==1.9.2
ydata-profiling==4.2.0
zict==3.0.0
zipp==3.11.0

Start with the BERTopic.transform API documentation and run the minimal example in the issue using the provided Python environment. Compare single-document and batch predictions across the reproduced differing entries; done means the behavior is explained and, if confirmed as a bug, the two invocation forms produce consistent topics.